LGR22’s Section 2 is the ‘glue’ that makes separate subjects feel like one coherent education. It is also the part many teams ‘agree with’ but struggle to show in day-to-day planning. Inspectors are rarely looking for a glossy cross-curricular project week. They are looking for a believable thread: shared language, consistent routines, and clear progression in how pupils meet values, democracy, sustainable development, and language-and-knowledge development across subjects.
In practical terms, that means you need to evidence three things. First, coherence: pupils should recognise the same ideas and expectations turning up in different rooms. Second, progression: the same theme should deepen over time, not reset each term. Third, shared language: staff and pupils can name what they are doing, why, and how it connects. If you want a wider start-of-year set-up that stays realistic, it helps to pair this with a light-touch roll-out model such as a minimum viable back-to-school AI toolkit rather than a full reinvention of planning.
You can set a whole-school cross-curricular culture in 60–90 minutes if you treat it as a ‘throughline alignment’ meeting, not a curriculum rewrite. The goal is to leave with a small set of shared statements and artefacts that subject teams can attach to existing schemes of work.
Begin with four Section 2 anchors on a single page: värdegrund, demokratiuppdrag, hållbar utveckling, and språk- och kunskapsutvecklande arbetssätt. Then agree one staff-facing sentence and one pupil-facing sentence for each. For example, ‘We practise democratic participation by taking roles, listening actively, and justifying decisions with evidence’ becomes ‘In lessons, we take turns, use reasons, and make fair decisions.’ Those two sentences become your shared language.
Next, each subject team chooses one unit in the first half-term where the anchor can be made visible with minimal disruption. This is important: you are not asking teams to squeeze in extra content. You are asking them to reveal what is already there, and to tighten the language so pupils can transfer it. If you are planning this session on an INSET day, you may find it useful to borrow the pacing and safety structures from an INSET-day AI workshop so the conversation stays practical.
The four AI micro-tools below work because they are small: they produce draft artefacts that teachers edit, then save as evidence. To keep this inspection-ready, you also need boundaries that are easy to explain to pupils, families, and colleagues.
Use minimum-data rules. Avoid pasting anything that identifies a child, a colleague, or a sensitive situation. Do not paste safeguarding notes, health information, behaviour incident details, or photographs of pupils’ work with names. If you want a quick staff-facing reference, align this with your annual AI acceptable use policy refresh checklist so expectations are consistent.
Add a transparency note to the front of your planning templates: ‘AI may be used to generate first drafts of lesson materials. Teachers review, adapt, and take responsibility for final content. No pupil personal data is entered into AI tools.’ This is not theatre; it is how you make professional judgement visible.
Finally, agree what not to paste. A simple rule is: if you would not email it to the wrong person by mistake, do not paste it into an AI tool. If you need a deeper compliance conversation, especially for EU contexts, keep a link to your internal guidance and consider a staff briefing based on an EU AI Act and LGR22 compliance explainer.
A maths teacher wants a sustainability data lesson without bolting on a separate ‘theme’. The micro-tool here is a Lesson Planner prompt that turns an existing data topic into a coherent Section 2 moment.
Inputs might include: year group, topic (mean/median/range), time (60 minutes), prior knowledge, and a sustainability context that is non-personal and global (for example, local rainfall, school energy-use totals without identifying classes, or publicly available CO₂ datasets). Add the Section 2 anchors you want to surface: hållbar utveckling plus språk- och kunskapsutvecklande arbetssätt.
Outputs you want: a lesson sequence with a short values link, explicit vocabulary, and a talk routine. For example, pupils interpret two graphs about energy use, then use a ‘claim–evidence–reasoning’ sentence frame to justify which intervention would reduce consumption most. The teacher edits to ensure the dataset is appropriate, checks misconceptions, and adjusts challenge.
Evidence to save is simple and inspection-friendly: the AI draft prompt and output (dated), the teacher’s edited lesson plan, and one slide or worksheet showing the shared language (for instance, the same ‘claim–evidence–reasoning’ frame used in science and humanities). A short reflection line after teaching—what pupils found hard, and what you will revisit—helps show progression rather than a one-off.
For democracy and citizenship, the micro-tool is a Unit Planner that coordinates roles, sequence, and assessment evidence across subjects without forcing identical lessons. Imagine a three-week unit where Swedish, social studies, and art each keep their subject integrity but share a democratic participation routine.
Inputs: participating subjects, available lessons, one core question (‘How should communities decide what is fair?’), and the Section 2 anchors (demokratiuppdrag and värdegrund). Ask the tool to propose roles pupils will practise repeatedly: chair, summariser, evidence-checker, and inclusion monitor. Then ask for a sequence where each subject uses the roles at least twice, so pupils build fluency.
Outputs: a unit map with a shared routine (for example, structured discussion with a visible talk protocol), and assessment evidence that is not just a final product. Include pupil voice: a short exit ticket after discussions (‘Which role helped your group most today, and why?’) and one mid-unit pulse check on whether pupils feel heard.
Teacher edits matter most here. You will adjust for timetable realities, ensure accessibility, and decide where assessment sits. Evidence to save includes the unit overview, the shared talk protocol, and a sample of anonymised pupil voice notes. This is the kind of coherence inspectors can recognise quickly because it shows a throughline, not a poster.
‘Sustainable development’ can become a slogan unless pupils meet it at the right level of abstraction. The micro-tool is a Concept Explainer that generates age-appropriate explanations, plus language scaffolds for SVA, and links across SO/SNO without collapsing them into one subject.
Inputs: age range, reading level, key vocabulary, and misconceptions to avoid (for example, ‘recycling solves everything’ or ‘sustainability means never using resources’). Ask for three versions: early years/primary, lower secondary, and an SVA-friendly version with sentence starters and cognates where appropriate.
Outputs should include: a concise definition, a concrete example pupils can picture, and a question that invites reasoning. A lower secondary version might connect environmental, social, and economic dimensions through a local planning scenario. The SVA version might add a dual-coded vocabulary box and sentence frames for comparing options.
Teacher edits ensure cultural relevance and accuracy, and you can embed the explainer into existing displays or knowledge organisers. If you are building shared vocabulary across corridors, it pairs well with approaches in AI-inclusive classroom displays, where the same terms reappear in multiple contexts.
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Retrieval is powerful, but cross-curricular quizzes often slip into trivia. The micro-tool here is a Quiz Generator that checks transfer: can pupils use a concept learned in one subject to reason in another?
Inputs: the four Section 2 anchors, two or three key concepts (for example, ‘evidence’, ‘trade-off’, ‘rights and responsibilities’), and the units pupils have just studied. Ask for questions that require explanation, not recall alone. A good item might present a short scenario about a school council decision on waste reduction and ask pupils to identify the trade-off, justify a choice using evidence, and name which democratic norm is being practised.
Moderation steps keep this safe and rigorous. Teachers should check reading load, bias, and whether a question accidentally assesses background knowledge rather than taught content. Agree a quick moderation routine: one colleague scans for accessibility, another for subject accuracy, and a third for values and inclusion. If you want to build staff confidence in discussing tricky edge cases, keep a route into your AI ethics classroom kit so decisions feel shared rather than personal.
An evidence pack should be light, searchable, and easy to explain. Aim for a single folder per term with subfolders for each anchor. Save: the one-page throughline statements, the shared talk protocol, one example lesson plan, one unit map, one concept explainer, and one moderated retrieval quiz. Add a short ‘what changed’ note per subject team: two or three sentences is enough.
Screenshot or export the AI outputs alongside the teacher-edited versions so it is clear where professional judgement happened. Store files in your normal planning space, not a personal drive, and use a simple sign-off chain: the subject lead checks alignment, a mentor or phase lead checks consistency, and a member of SLT samples for coherence. If you are already running early-term stability checks, you can align this pack with your broader first-month routines, similar to those discussed in a September stability map for AI in schools, while keeping the focus on learning rather than tools.
Week one is alignment and language. Run the 60–90 minute throughline meeting, agree the four anchor statements, and choose one early unit per subject to ‘make visible’. Week two is small production. Each team uses the Lesson Planner or Unit Planner once, then edits and teaches one lesson with the shared talk routine and vocabulary. Week three is consolidation. Introduce the Concept Explainer versions and place the shared vocabulary where pupils will actually see it, then run one moderated transfer quiz. Week four is evidence and refinement. Assemble the evidence pack, collect a small sample of pupil voice, and agree one tweak per team for the next unit.
A ‘stop doing’ list is what protects workload. Stop rewriting schemes of work to ‘add’ Section 2. Stop creating new cross-curricular projects just to prove you did something. Stop collecting excessive evidence; save artefacts that show coherence and progression. Stop using AI for anything involving identifiable pupil information. When the throughline is working, it should feel like better teaching habits, not extra initiatives.
May your cross-curricular threads stay visible, teachable, and easy to evidence this term. The Automated Education Team
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